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Investigating the impact of mindfulness meditation training on working memory: a mathematical modeling approach.

机译:研究正念冥想训练对工作记忆的影响:一种数学建模方法。

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We investigated whether mindfulness training (MT) influences information processing in a working memory task with complex visual stimuli. Participants were tested before (T1) and after (T2) participation in an intensive one-month MT retreat, and their performance was compared with that of an age- and education-matched control group. Accuracy did not differ across groups at either time point. Response times were faster and significantly less variable in the MT versus the control group at T2. Since these results could be due to changes in mnemonic processes, speed-accuracy trade-off, or nondecisional factors (e.g., motor execution), we used a mathematical modeling approach to disentangle these factors. The EZ-diffusion model (Wagenmakers, van der Maas, & Grasman, Psychonomic Bulletin & Review 14:(1), 3-22, 2007) suggested that MT leads to improved information quality and reduced response conservativeness, with no changes in nondecisional factors. The noisy exemplar model further suggested that the increase in information quality reflected a decrease in encoding noise and not an increase in forgetting. Thus, mathematical modeling may help clarify the mechanisms by which MT produces salutary effects on performance.
机译:我们调查了正念训练(MT)是否会影响具有复杂视觉刺激的工作记忆任务中的信息处理。在一个密集的1个月MT撤退之前(T1)和之后(T2)对参与者进行了测试,并将他们的表现与年龄和文化程度相匹配的对照组进行了比较。在两个时间点上,各组的准确性均没有差异。与T2对照组相比,MT的响应时间更快,并且变化明显更少。由于这些结果可能是由于助记符过程的变化,速度准确性的权衡或非决定性因素(例如,运动执行)导致的,因此我们使用数学建模方法来解开这些因素。 EZ扩散模型(Wagenmakers,van der Maas和Grasman,Psychonomic Bulletin&Review 14:(1),2007年3月22日)表明,MT可以提高信息质量,并降低响应保守性,并且非决定性因素没有变化。 。嘈杂的示例模型进一步表明,信息质量的提高反映了编码噪声的减少,而不是遗忘的增加。因此,数学建模可以帮助阐明MT对性能产生有益影响的机制。

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